The increase in the demand for computers and other digital systems, such as cell phones and personal digital assistants (PDAs), has resulted in a corresponding increase in the competition between systems manufacturers for market share. In order to better compete, manufacturers of such systems continue to develop techniques for testing systems in order to identify systems that have failed during the manufacturing process, thus improving the quality of the delivered products and furthering the reputation of the manufacturer. But such a reputation can also be damaged by systems that function at delivery, but fail shortly afterward, a failure sometimes referred to as “infant mortality.” These infant mortality failures also result in additional expenditures in the form of warranty related servicing, repairs and/or replacements. To avoid shipping systems with such “latent” failures, techniques have been developed to test systems and identify what are sometimes referred to as “statistical outliers,” wherein a given system passes a functional test, but differs significantly in its test results as compared to the statistical norm for a given group of manufactured systems. Depending on the nature and degree of the difference in the test results, it may be possible to correlate such statistical anomalies to future failures.
But the use of statistical testing anomalies as predictors of future failures can require that highly specialized testing be performed on each system during various stages of production, sometimes by sophisticated and expensive testing systems, adding to the overall production time and cost. Further, because each type of system may have a different configuration or design, unique testing systems and programs may have to be developed for each platform, adding to the overall product development time and cost as well.